Genotype-environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence.

Identifying areas of high evolutionary potential is a judicious strategy for developing conservation priorities in the face of environmental change. For wide-ranging species occupying heterogeneous environments, the evolutionary forces that shape distinct populations can vary spatially. Here, we investigate patterns of genomic variation and genotype-environment associations in the hermit thrush (Catharus guttatus), a North American songbird, at broad (across the breeding range) and narrow spatial scales (at a hybrid zone). We begin by building a genoscape or map of genetic variation across the breeding range and find five distinct genetic clusters within the species, with the greatest variation occurring in the western portion of the range. Genotype-environment association analyses indicate higher allelic turnover in the west than in the east, with measures of temperature surfacing as key predictors of putative adaptive genomic variation rangewide. Since broad patterns detected across a species' range represent the aggregate of many locally adapted populations, we investigate whether our broadscale analysis is consistent with a finer scale analysis. We find that top rangewide temperature-associated loci vary in their clinal patterns (e.g., steep clines vs. fixed allele frequencies) across a hybrid zone in British Columbia, suggesting that the environmental predictors and the associated candidate loci identified in the rangewide analysis are of variable importance in this particular region. However, two candidate loci exhibit strong concordance with the temperature gradient in British Columbia, suggesting a potential role for temperature-related barriers to gene flow and/or temperature-driven ecological selection in maintaining putative local adaptation. This study demonstrates how patterns identified at the broad (macrogeographic) scale can be validated by investigating genotype-environment correlations at the local (microgeographic) scale. Furthermore, our results highlight the importance of considering the spatial distribution of putative adaptive variation when assessing population-level sensitivity to climate change and other stressors.

Integrative tracking methods elucidate the evolutionary dynamics of a migratory divide.

Migratory divides, the boundary between adjacent bird populations that migrate in different directions, are of considerable interest to evolutionary biologists because of their alleged role in speciation of migratory birds. However, the small size of many passerines has traditionally limited the tools available to track populations and as a result, restricted our ability to study how reproductive isolation might occur across a divide. Here, we integrate multiple approaches by using genetic, geolocator, and morphological data to investigate a migratory divide in hermit thrushes (Catharus guttatus). First, high genetic divergence between migratory groups indicates the divide is a region of secondary contact between historically isolated populations. Second, despite low sample sizes, geolocators reveal dramatic differences in overwintering locations and migratory distance of individuals from either side of the divide. Third, a diagnostic genetic marker that proved useful for tracking a key population suggests a likely intermediate nonbreeding location of birds from the hybrid zone. This finding, combined with lower return rates from this region, is consistent with comparatively lower fitness of hybrids, which is possibly due to this intermediate migration pattern. We discuss our results in the context of reproductive isolating mechanisms associated with migration patterns that have long been hypothesized to promote divergence across migratory divides.

Novel statistical methods for integrating genetic and stable isotope data to infer individual-level migratory connectivity.

Methods for determining patterns of migratory connectivity in animal ecology have historically been limited due to logistical challenges. Recent progress in studying migratory bird connectivity has been made using genetic and stable-isotope markers to assign migratory individuals to their breeding grounds. Here, we present a novel Bayesian approach to jointly leverage genetic and isotopic markers and we test its utility on two migratory passerine bird species. Our approach represents a principled model-based combination of genetic and isotope data from samples collected on the breeding grounds and is able to achieve levels of assignment accuracy that exceed those of either method alone. When applied at large scale the method can reveal specific migratory connectivity patterns. In Wilson's warblers (Wilsonia pusilla), we detect a subgroup of birds wintering in Baja that uniquely migrate preferentially from the coastal Pacific Northwest. Our approach is implemented in a way that is easily extended to accommodate additional sources of information (e.g. bi-allelic markers, species distribution models, etc.) or adapted to other species or assignment problems.